Quantitative assessment of Pb sources in urban-rural river sediments based on Pb isotopes and PMF, MixSIAR models

Abstract

The complex land use in urban-rural rivers and the diverse point and non-point source pollutions pose challenges to tracing the sources of heavy metal pollution in river sediments. Therefore, this study used the combination of Pb stable isotopes, positive matrix factorization (PMF) model and Bayesian mixture model (MixSIAR) to clarify the contents of As, Cr, Cd, Mn, Cu, Zn, Ni and Pb and the distribution characteristics of Pb isotopes in the sediments of a typical urban-rural river (Yinghe river). The sources of heavy metals in sediments were quantitatively identified, and the contribution characteristics of multi-source Pb pollution were revealed. The results showed that the mean values of all heavy metals except Cr and Mn exceeded the local soil background values. Four potential sources of heavy metals were identified based on PMF: Cr and Mn were mainly from natural sources (19.6%), Cd, Pb, and Ni were closely related to industrial sources (32.1%), As, Pb, and Zn were closely related to agricultural sources (28%), and Cu and Zn were closely related to traffic sources (20.3%). In addition, the contribution of multiple Pb pollution sources was determined by combining Pb stable isotopes and MixSIAR: agricultural sources (32.1%), industrial sources (30.5%), traffic sources (27.2%), and natural sources (10.3%). The difference in the contribution rates of PMF and MixSIAR for quantitative analysis of Pb pollution sources was less than 10%, which proved the reliability of the model. At the same time, according to the significant correlation between Pb pollution and land use pattern in Yinghe river, corresponding pollution prevention strategies were put forward. The results provided a new perspective for identifying the quantitative source of heavy metal pollution in urban-rural rivers sediments, and provided support for the management and prevention of river heavy metals.